Sustainability is the current theme of global development, and for China, it is not only an opportunity but also a challenge. In 2016, the Paris Agreement on climate change was adopted, addressing the need to limit th...Sustainability is the current theme of global development, and for China, it is not only an opportunity but also a challenge. In 2016, the Paris Agreement on climate change was adopted, addressing the need to limit the rise of global temperatures. The United Nations(UN) has set Sustainable Development Goals(SDGs) to transform our world in terms of closely linking human well-being, economic prosperity, and healthy environments. Sustainable development requires the support of spatial information and objective evaluation,and the capability of macroscopic, rapid, accurate Earth observation techniques plays an important role in sustainable development. Recently, Earth observation technologies are developing rapidly in China, where scientists are building coordinated, comprehensive and sustainable Earth observation systems for global monitoring programs. Recent efforts include the Digital Belt and Road Program(DBAR) and comparative studies of the "three poles". This and other researches will provide powerful support for solving problems such as global change and environmental degradation.展开更多
Human beings are now facing global and regional sustainable development challenges.In China, Earth observation data play a fundamental role in Earth system science research. The support given by Earth observation data...Human beings are now facing global and regional sustainable development challenges.In China, Earth observation data play a fundamental role in Earth system science research. The support given by Earth observation data is required by many studies, including those on Earth's limited natural resources, the rapid development of economic and social needs, global change, extreme events, food security, water resources, sustainable economic and urban development, and emergency response. Application operation systems in many ministries and departments in China have entered a stage of sustainable development, and the State Key Project of High-Resolution Earth Observation Systems has been progressing since 2006. Earth observation technology in China has entered a period of rapid development.展开更多
The brokering approach can be successfully used to overcome the crucial question of searching among enormous amount of data （raw and/or processed） produced and stored in different information systems. In this paper,...The brokering approach can be successfully used to overcome the crucial question of searching among enormous amount of data （raw and/or processed） produced and stored in different information systems. In this paper, authors describe the Data Management System the DMS （Data Management System） developed by INGV （Istituto Nazionale di Geofisica e Vulcanologia） to support the brokering system GEOSS （Global Earth Observation System of Systems） adopted for the ARCA （Arctic Present Climate Change and Past Extreme Events） project. This DMS includes heterogeneous data that contributes to the ARCA objective （www.arcaproject.it） focusing on multi-parametric and multi-disciplinary studies on the mechanism （s） behind the release of large volumes of cold and fresh water from melting of ice caps. The DMS is accessible directly at the www.arca.rm.ingv.it, or through the IADC （Italian Arctic Data Center） at http：//arcticnode.dta.cnr.it/iadc/gi-portal/index.jsp that interoperates with the GEOSS brokering system （http：//www.geoportal.org0 making easy and fast the search of specific data set and its URL.展开更多
地球观测组织GEO(Group on Earth Observations)是地球观测领域规模最大和最具影响力的政府间国际组织,中国是地球观测组织创始国之一,自2005年地球观测组织成立起一直担任代表发展中国家和亚洲大洋洲区域的联合主席国。本文对地球观测...地球观测组织GEO(Group on Earth Observations)是地球观测领域规模最大和最具影响力的政府间国际组织,中国是地球观测组织创始国之一,自2005年地球观测组织成立起一直担任代表发展中国家和亚洲大洋洲区域的联合主席国。本文对地球观测组织过去18年的发展实践历程进行了回顾与总结,论述了中国在国内、亚洲大洋洲和国际3个层面的相关工作成果,从治理机制、项目合作、公共产品、人才队伍4个方面设计了中国未来参与地球观测组织全球治理,加速融入全球创新网络,携手构建全球科技共同体的工作内容体系。展开更多
甚长基线干涉测量(very long baseline interferometry,VLBI)是测量地球定向参数(earth orientation parameters,EOP)的主要空间测地技术之一,中国正在建设名为VLBI全球观测系统(VLBI global observing system,VGOS)的新一代测地VLBI站...甚长基线干涉测量(very long baseline interferometry,VLBI)是测量地球定向参数(earth orientation parameters,EOP)的主要空间测地技术之一,中国正在建设名为VLBI全球观测系统(VLBI global observing system,VGOS)的新一代测地VLBI站,通过国际联测优化站网构型是实现高精度EOP测量的必由之路。以3个中国VGOS站为核心站,通过引入2个国外站构建5站联合观测网,分析评估了不同站网构型的EOP测量能力。针对每个站网构型,通过调整4个约束条件的权重因子批量生成相应的观测纲要,采用蒙特卡洛仿真方法选择最优的观测纲要,评价指标为EOP解算值的可重复性。仿真结果表明,由中国站、南非哈特比站以及澳大利亚霍巴特站组成的网型EOP测量能力最强,相对于中国3站组成的网型,dUT1测量精度提高5.7倍,极移的X、Y分量的测量精度分别提高2.8倍和18.3倍。仿真结果可为后续开展高精度EOP组网观测提供参考依据。展开更多
Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this two-part paper identifies an innovative,but realistic EO optical sensory imagederived semantics-enriched An...Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this two-part paper identifies an innovative,but realistic EO optical sensory imagederived semantics-enriched Analysis Ready Data(ARD)productpair and process gold standard as linchpin for success of a new notion of Space Economy 4.0.To be implemented in operational mode at the space segment and/or midstream segment by both public and private EO big data providers,it is regarded as necessarybut-not-sufficient“horizontal”(enabling)precondition for:(I)Transforming existing EO big raster-based data cubes at the midstream segment,typically affected by the so-called data-rich information-poor syndrome,into a new generation of semanticsenabled EO big raster-based numerical data and vector-based categorical(symbolic,semi-symbolic or subsymbolic)information cube management systems,eligible for semantic content-based image retrieval and semantics-enabled information/knowledge discovery.(II)Boosting the downstream segment in the development of an ever-increasing ensemble of“vertical”(deep and narrow,user-specific and domain-dependent)value–adding information products and services,suitable for a potentially huge worldwide market of institutional and private end-users of space technology.For the sake of readability,this paper consists of two parts.In the present Part 1,first,background notions in the remote sensing metascience domain are critically revised for harmonization across the multidisciplinary domain of cognitive science.In short,keyword“information”is disambiguated into the two complementary notions of quantitative/unequivocal information-as-thing and qualitative/equivocal/inherently ill-posed information-as-data-interpretation.Moreover,buzzword“artificial intelligence”is disambiguated into the two better-constrained notions of Artificial Narrow Intelligence as part-without-inheritance-of AGI.Second,based on a betterdefined and better-understood vocabulary of multidisciplinary terms,existing EO optical sensory image-derived Level 2/ARD products and processes are investigated at the Marr five levels of understanding of an information processing system.To overcome their drawbacks,an innovative,but realistic EO optical sensory image-derived semantics-enriched ARD product-pair and process gold standard is proposed in the subsequent Part 2.展开更多
Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this paper consists of two parts.In the previous Part 1,existing EO optical sensory imagederived Level 2/Analysi...Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this paper consists of two parts.In the previous Part 1,existing EO optical sensory imagederived Level 2/Analysis Ready Data(ARD)products and processes are critically compared,to overcome their lack of harmonization/standardization/interoperability and suitability in a new notion of Space Economy 4.0.In the present Part 2,original contributions comprise,at the Marr five levels of system understanding:(1)an innovative,but realistic EO optical sensory image-derived semantics-enriched ARD co-product pair requirements specification.First,in the pursuit of third-level semantic/ontological interoperability,a novel ARD symbolic(categorical and semantic)co-product,known as Scene Classification Map(SCM),adopts an augmented Cloud versus Not-Cloud taxonomy,whose Not-Cloud class legend complies with the standard fully-nested Land Cover Classification System’s Dichotomous Phase taxonomy proposed by the United Nations Food and Agriculture Organization.Second,a novel ARD subsymbolic numerical co-product,specifically,a panchromatic or multispectral EO image whose dimensionless digital numbers are radiometrically calibrated into a physical unit of radiometric measure,ranging from top-of-atmosphere reflectance to surface reflectance and surface albedo values,in a five-stage radiometric correction sequence.(2)An original ARD process requirements specification.(3)An innovative ARD processing system design(architecture),where stepwise SCM generation and stepwise SCM-conditional EO optical image radiometric correction are alternated in sequence.(4)An original modular hierarchical hybrid(combined deductive and inductive)computer vision subsystem design,provided with feedback loops,where software solutions at the Marr two shallowest levels of system understanding,specifically,algorithm and implementation,are selected from the scientific literature,to benefit from their technology readiness level as proof of feasibility,required in addition to proven suitability.To be implemented in operational mode at the space segment and/or midstream segment by both public and private EO big data providers,the proposed EO optical sensory image-derived semantics-enriched ARD product-pair and process reference standard is highlighted as linchpin for success of a new notion of Space Economy 4.0.展开更多
文摘Sustainability is the current theme of global development, and for China, it is not only an opportunity but also a challenge. In 2016, the Paris Agreement on climate change was adopted, addressing the need to limit the rise of global temperatures. The United Nations(UN) has set Sustainable Development Goals(SDGs) to transform our world in terms of closely linking human well-being, economic prosperity, and healthy environments. Sustainable development requires the support of spatial information and objective evaluation,and the capability of macroscopic, rapid, accurate Earth observation techniques plays an important role in sustainable development. Recently, Earth observation technologies are developing rapidly in China, where scientists are building coordinated, comprehensive and sustainable Earth observation systems for global monitoring programs. Recent efforts include the Digital Belt and Road Program(DBAR) and comparative studies of the "three poles". This and other researches will provide powerful support for solving problems such as global change and environmental degradation.
文摘Human beings are now facing global and regional sustainable development challenges.In China, Earth observation data play a fundamental role in Earth system science research. The support given by Earth observation data is required by many studies, including those on Earth's limited natural resources, the rapid development of economic and social needs, global change, extreme events, food security, water resources, sustainable economic and urban development, and emergency response. Application operation systems in many ministries and departments in China have entered a stage of sustainable development, and the State Key Project of High-Resolution Earth Observation Systems has been progressing since 2006. Earth observation technology in China has entered a period of rapid development.
文摘The brokering approach can be successfully used to overcome the crucial question of searching among enormous amount of data （raw and/or processed） produced and stored in different information systems. In this paper, authors describe the Data Management System the DMS （Data Management System） developed by INGV （Istituto Nazionale di Geofisica e Vulcanologia） to support the brokering system GEOSS （Global Earth Observation System of Systems） adopted for the ARCA （Arctic Present Climate Change and Past Extreme Events） project. This DMS includes heterogeneous data that contributes to the ARCA objective （www.arcaproject.it） focusing on multi-parametric and multi-disciplinary studies on the mechanism （s） behind the release of large volumes of cold and fresh water from melting of ice caps. The DMS is accessible directly at the www.arca.rm.ingv.it, or through the IADC （Italian Arctic Data Center） at http：//arcticnode.dta.cnr.it/iadc/gi-portal/index.jsp that interoperates with the GEOSS brokering system （http：//www.geoportal.org0 making easy and fast the search of specific data set and its URL.
文摘地球观测组织GEO(Group on Earth Observations)是地球观测领域规模最大和最具影响力的政府间国际组织,中国是地球观测组织创始国之一,自2005年地球观测组织成立起一直担任代表发展中国家和亚洲大洋洲区域的联合主席国。本文对地球观测组织过去18年的发展实践历程进行了回顾与总结,论述了中国在国内、亚洲大洋洲和国际3个层面的相关工作成果,从治理机制、项目合作、公共产品、人才队伍4个方面设计了中国未来参与地球观测组织全球治理,加速融入全球创新网络,携手构建全球科技共同体的工作内容体系。
文摘甚长基线干涉测量(very long baseline interferometry,VLBI)是测量地球定向参数(earth orientation parameters,EOP)的主要空间测地技术之一,中国正在建设名为VLBI全球观测系统(VLBI global observing system,VGOS)的新一代测地VLBI站,通过国际联测优化站网构型是实现高精度EOP测量的必由之路。以3个中国VGOS站为核心站,通过引入2个国外站构建5站联合观测网,分析评估了不同站网构型的EOP测量能力。针对每个站网构型,通过调整4个约束条件的权重因子批量生成相应的观测纲要,采用蒙特卡洛仿真方法选择最优的观测纲要,评价指标为EOP解算值的可重复性。仿真结果表明,由中国站、南非哈特比站以及澳大利亚霍巴特站组成的网型EOP测量能力最强,相对于中国3站组成的网型,dUT1测量精度提高5.7倍,极移的X、Y分量的测量精度分别提高2.8倍和18.3倍。仿真结果可为后续开展高精度EOP组网观测提供参考依据。
文摘Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this two-part paper identifies an innovative,but realistic EO optical sensory imagederived semantics-enriched Analysis Ready Data(ARD)productpair and process gold standard as linchpin for success of a new notion of Space Economy 4.0.To be implemented in operational mode at the space segment and/or midstream segment by both public and private EO big data providers,it is regarded as necessarybut-not-sufficient“horizontal”(enabling)precondition for:(I)Transforming existing EO big raster-based data cubes at the midstream segment,typically affected by the so-called data-rich information-poor syndrome,into a new generation of semanticsenabled EO big raster-based numerical data and vector-based categorical(symbolic,semi-symbolic or subsymbolic)information cube management systems,eligible for semantic content-based image retrieval and semantics-enabled information/knowledge discovery.(II)Boosting the downstream segment in the development of an ever-increasing ensemble of“vertical”(deep and narrow,user-specific and domain-dependent)value–adding information products and services,suitable for a potentially huge worldwide market of institutional and private end-users of space technology.For the sake of readability,this paper consists of two parts.In the present Part 1,first,background notions in the remote sensing metascience domain are critically revised for harmonization across the multidisciplinary domain of cognitive science.In short,keyword“information”is disambiguated into the two complementary notions of quantitative/unequivocal information-as-thing and qualitative/equivocal/inherently ill-posed information-as-data-interpretation.Moreover,buzzword“artificial intelligence”is disambiguated into the two better-constrained notions of Artificial Narrow Intelligence as part-without-inheritance-of AGI.Second,based on a betterdefined and better-understood vocabulary of multidisciplinary terms,existing EO optical sensory image-derived Level 2/ARD products and processes are investigated at the Marr five levels of understanding of an information processing system.To overcome their drawbacks,an innovative,but realistic EO optical sensory image-derived semantics-enriched ARD product-pair and process gold standard is proposed in the subsequent Part 2.
基金ASAP 16 project call,project title:SemantiX-A cross-sensor semantic EO data cube to open and leverage essential climate variables with scientists and the public,Grant ID:878939ASAP 17 project call,project title:SIMS-Soil sealing identification and monitoring system,Grant ID:885365.
文摘Aiming at the convergence between Earth observation(EO)Big Data and Artificial General Intelligence(AGI),this paper consists of two parts.In the previous Part 1,existing EO optical sensory imagederived Level 2/Analysis Ready Data(ARD)products and processes are critically compared,to overcome their lack of harmonization/standardization/interoperability and suitability in a new notion of Space Economy 4.0.In the present Part 2,original contributions comprise,at the Marr five levels of system understanding:(1)an innovative,but realistic EO optical sensory image-derived semantics-enriched ARD co-product pair requirements specification.First,in the pursuit of third-level semantic/ontological interoperability,a novel ARD symbolic(categorical and semantic)co-product,known as Scene Classification Map(SCM),adopts an augmented Cloud versus Not-Cloud taxonomy,whose Not-Cloud class legend complies with the standard fully-nested Land Cover Classification System’s Dichotomous Phase taxonomy proposed by the United Nations Food and Agriculture Organization.Second,a novel ARD subsymbolic numerical co-product,specifically,a panchromatic or multispectral EO image whose dimensionless digital numbers are radiometrically calibrated into a physical unit of radiometric measure,ranging from top-of-atmosphere reflectance to surface reflectance and surface albedo values,in a five-stage radiometric correction sequence.(2)An original ARD process requirements specification.(3)An innovative ARD processing system design(architecture),where stepwise SCM generation and stepwise SCM-conditional EO optical image radiometric correction are alternated in sequence.(4)An original modular hierarchical hybrid(combined deductive and inductive)computer vision subsystem design,provided with feedback loops,where software solutions at the Marr two shallowest levels of system understanding,specifically,algorithm and implementation,are selected from the scientific literature,to benefit from their technology readiness level as proof of feasibility,required in addition to proven suitability.To be implemented in operational mode at the space segment and/or midstream segment by both public and private EO big data providers,the proposed EO optical sensory image-derived semantics-enriched ARD product-pair and process reference standard is highlighted as linchpin for success of a new notion of Space Economy 4.0.
